Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review

Depression is a common mental health disorder that affects an individual’s moods, thought processes and behaviours negatively, and disrupts one’s ability to function optimally. In most cases, people with depression try to hide their symptoms and refrain from obtaining professional help due to the st...

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Autores principales:	Isuri Anuradha Nanomi Arachchige, Priyadharshany Sandanapitchai, Ruvan Weerasinghe
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	information extraction machine learning depression identification online forum mining Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/cd50d9b22ad841b093caf1a498131eb2
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spelling	oai:doaj.org-article:cd50d9b22ad841b093caf1a498131eb22021-11-25T17:58:26ZInvestigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review10.3390/info121104442078-2489https://doaj.org/article/cd50d9b22ad841b093caf1a498131eb22021-10-01T00:00:00Zhttps://www.mdpi.com/2078-2489/12/11/444https://doaj.org/toc/2078-2489Depression is a common mental health disorder that affects an individual’s moods, thought processes and behaviours negatively, and disrupts one’s ability to function optimally. In most cases, people with depression try to hide their symptoms and refrain from obtaining professional help due to the stigma related to mental health. The digital footprint we all leave behind, particularly in online support forums, provides a window for clinicians to observe and assess such behaviour in order to make potential mental health diagnoses. Natural language processing (NLP) and Machine learning (ML) techniques are able to bridge the existing gaps in converting language to a machine-understandable format in order to facilitate this. Our objective is to undertake a systematic review of the literature on NLP and ML approaches used for depression identification on Online Support Forums (OSF). A systematic search was performed to identify articles that examined ML and NLP techniques to identify depression disorder from OSF. Articles were selected according to the PRISMA workflow. For the purpose of the review, 29 articles were selected and analysed. From this systematic review, we further analyse which combination of features extracted from NLP and ML techniques are effective and scalable for state-of-the-art Depression Identification. We conclude by addressing some open issues that currently limit real-world implementation of such systems and point to future directions to this end.Isuri Anuradha Nanomi ArachchigePriyadharshany SandanapitchaiRuvan WeerasingheMDPI AGarticleinformation extractionmachine learningdepression identificationonline forum miningInformation technologyT58.5-58.64ENInformation, Vol 12, Iss 444, p 444 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	information extraction machine learning depression identification online forum mining Information technology T58.5-58.64
spellingShingle	information extraction machine learning depression identification online forum mining Information technology T58.5-58.64 Isuri Anuradha Nanomi Arachchige Priyadharshany Sandanapitchai Ruvan Weerasinghe Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review
description	Depression is a common mental health disorder that affects an individual’s moods, thought processes and behaviours negatively, and disrupts one’s ability to function optimally. In most cases, people with depression try to hide their symptoms and refrain from obtaining professional help due to the stigma related to mental health. The digital footprint we all leave behind, particularly in online support forums, provides a window for clinicians to observe and assess such behaviour in order to make potential mental health diagnoses. Natural language processing (NLP) and Machine learning (ML) techniques are able to bridge the existing gaps in converting language to a machine-understandable format in order to facilitate this. Our objective is to undertake a systematic review of the literature on NLP and ML approaches used for depression identification on Online Support Forums (OSF). A systematic search was performed to identify articles that examined ML and NLP techniques to identify depression disorder from OSF. Articles were selected according to the PRISMA workflow. For the purpose of the review, 29 articles were selected and analysed. From this systematic review, we further analyse which combination of features extracted from NLP and ML techniques are effective and scalable for state-of-the-art Depression Identification. We conclude by addressing some open issues that currently limit real-world implementation of such systems and point to future directions to this end.
format	article
author	Isuri Anuradha Nanomi Arachchige Priyadharshany Sandanapitchai Ruvan Weerasinghe
author_facet	Isuri Anuradha Nanomi Arachchige Priyadharshany Sandanapitchai Ruvan Weerasinghe
author_sort	Isuri Anuradha Nanomi Arachchige
title	Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review
title_short	Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review
title_full	Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review
title_fullStr	Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review
title_full_unstemmed	Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review
title_sort	investigating machine learning & natural language processing techniques applied for predicting depression disorder from online support forums: a systematic literature review
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/cd50d9b22ad841b093caf1a498131eb2
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Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review

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